Triple

T2068726
Position Surface form Disambiguated ID Type / Status
Subject Đan Phượng District E45965 entity
Predicate hasUrbanizationTrend P29003 FINISHED
Object increasing urban development LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: increasing urban development | Statement: [Đan Phượng District, hasUrbanizationTrend, increasing urban development]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUrbanizationTrend
Context triple: [Đan Phượng District, hasUrbanizationTrend, increasing urban development]
  • A. hasUrbanGrowthCharacteristic chosen
    Indicates that an entity exhibits a particular quality, pattern, or feature related to urban growth or expansion.
  • B. isUrbanized
    Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
  • C. urbanizationLevel
    Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
  • D. hasSuburbanGrowth
    Indicates that an area or entity is experiencing or characterized by expansion or development typical of suburban environments.
  • E. hasUrbanFunction
    Indicates that an entity serves a specific role or purpose within an urban context, such as providing services, infrastructure, or activities typical of a city environment.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a8891b38288190abd572ccad9b6928 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9f51a008190aead0173a9289204 completed March 7, 2026, 5:39 a.m.
PD Predicate disambiguation batch_69abb7aee9b48190999620176e3a6ee2 completed March 7, 2026, 5:29 a.m.
Created at: March 4, 2026, 7:41 p.m.